How to Generate Tests With AI

Writing test scripts can be one of the most tedious and time-consuming processes of software testing. When software applications scale or become more complex, it becomes harder to keep up with writing test scripts manually.

Relying on traditional testing methods will not give the speed at which modern software needs to be developed and released.

However, by using AI to generate tests, developers and testers can save time and effort, ensuring that all aspects of the software application are covered without constantly rewriting test cases. AI can help generate tests based on how software behaves, find potential issues, and improve overall test coverage—all while reducing human error.

In this blog, we look at how to generate tests with AI.

Why Generate Tests With AI?

Incorporating artificial intelligence to generate tests for automation testing can bring a lot of benefits:

• Tackle Complex Scenarios: Complex scenarios, such as analyzing the load threshold or performance metrics, including network latency in various network calls, can easily be done through AI. Testers can also create complex tests without worrying about their maintenance easily.
• Increased Test Coverage: AI is capable of scanning the test script and determining the areas that have not been covered through tests. Then, it can generate tests for those sections specifically and, in the process, increase the test coverage automatically.
• Early Bug Detection: To generate tests with AI is not the only thing a tester can do. AI can also be implemented as an assistant which can assist the entire coding process and predict bugs in the code as a tester is writing them. It facilitates bug detection at the earliest possible phase of testing.
• Ease of Management: As the software scales, it becomes a lot harder to manage every testing process, let alone test case management. Scalability brings its challenges, a lot of which can be eliminated with AI in the process.
• Accuracy: Automated testing is the execution of test scripts written in a programming language (scripted automation) or as instructions (codeless automation). When done manually, all of this requires time and complex logic, which can be flawed more often than we think.

AI helps generate test cases that can target each task as instructed by the tester. Yes, the tests can be complex here as well, but since AI maintains it, it is acceptable.

Generating test cases for automated testing is time-consuming and challenging. Testers must identify locators, initiate drivers, and write complex logic, all while uncertain about test coverage. Achieving 100% coverage manually is not feasible. AI steps in by automating test writing, analysis, coverage, and execution, saving time and allowing testers to focus on more critical tasks like usability testing and optimizing the software cycle.

Generating Tests With AI

To demonstrate how AI can help generate tests easily for automated software testing, let’s explore this with three different tools:

• KaneAI
• ChatGPT
• Claude

Generating Tests With KaneAI

KaneAI by LambdaTest is a smart AI test assistant for high-speed quality engineering teams. It lets you create, evolve and debug tests involving using natural language. It integrates seamlessly with the rest of LambdaTest’s offerings around test orchestration, execution and analysis.

Features:

• Create and evolve tests using natural language commands.
• Generate and execute test steps based on high-level objectives.
• Convert automated tests into all major languages and frameworks like Selenium and Playwright.
• Write or paste custom JavaScript code snippets to run tests.
• Perform scrolling actions on WebElements using natural language commands.
• Run tests with advanced configurations such as changing geolocation, testing on localhost servers using LambdaTest Tunnel and testing with a dedicated proxy.

Shown below are steps to generate tests with KaneAI:

Note: Make sure you have access to KaneAI. To get access, please contact sales.

1. From the LambdaTest dashboard, click the KaneAI option.



2. Click on the Create a Web Test button. It will open up the browser with a side panel available to write test cases.



It will initiate the browser agent and provide a separate panel to generate tests. The tester can choose to either write test cases here or interact with the application manually to generate test cases. Since we are discussing the role of artificial intelligence in automated software testing, let’s generate tests through manual mode.

3. Click on the Manual Interaction button.



4. Now, the tester can interact with the browser agent, and the test will be generated for their actions. For this demo, follow these steps:
1. Enter the URL www.lambdatest.com
2. Click on Resources
3. Click on Blog
4. Scroll down
5. Click on any blog

You can see all the above test steps (or actions) are converted to test cases:



As you can notice, AI has filled up all the required fields automatically to save tester time.

5. Click on the Finish Test button.
6. Select the Folder where you want to save tests and choose Type and Status. You can also modify other details if need be. Then, click on the Save Test Case button.



It will now redirect you to the LambdaTest Test Manager, where you can manage your test cases. You can also view other details like Summary, Code, Runs, Issues, and Version History.



7. To generate your tests for the above test cases, click on the Code tab.



You will notice the following options and go ahead with the one that you need:

• Generate new Code: Generates new code in a different language or framework for the same test case.
• HyperExecute: Triggers tests on the HyperExecute platform.
• View code: Opens the code in a built-in editor to edit code files and download them.
• Download: Lets you download the entire generated tests (with code files).

To get started, refer to this getting started guide on KaneAI.

Generating Tests With ChatGPT

ChatGPT is a Generative AI platform that takes a text-based input, analyzes it with natural language processing, and provides an output for the same. It can be used to generate tests with AI by simply asking the tool to generate test scripts directly.

For instance, let’s say you want to test whether a user can sign up using an existing email address.

1. Enter the above test scenario directly into the ChatGPT input field:



2. Press Enter to get the output. This is a complete test script (with comments) for the test scenario we requested. The whole process took less than 10 seconds which would have otherwise taken at least 15-20 minutes manually.



ChatGPT is an excellent way to generate tests with AI. However, the only downside is that the tester has to do some post-script generation work as well. For instance, here, they need to integrate this piece of code with their existing test suite and replace every variable accordingly.

It becomes complex as the suite grows. Also, ChatGPT can only help when automated testing is done in the scripted mode and not in codeless mode.

Generating Tests With Claude

Claude is an interesting approach to performing automation testing with the help of AI. It provides an input box, just like ChatGPT, where the tester can put down the scenario to perform, and Claude takes care of the rest.

It loves open-ended conversations, and therefore the tester need not follow a strict instruction-based approach in English. They can write a paragraph about what they want to do, and the tool will analyze, understand, and perform actions on it.

Claude is powerful and focused on transparency and accuracy. It can not only help perform certain automation tasks but can detect bugs and fix the errors in the codebase. All the tester needs to do is tell their query in the input field.

Just like ChatGPT, Claude, too is not limited to just code generation and analysis. You can perform almost any task using Claude, including providing a summary or understanding a piece of code written in any programming language.

The only downside to Claude (and also ChatGPT) is that it doesn’t provide a host or agent like KaneAI, where web and mobile applications can be tested. The testers have to integrate their system with another tool (such as Puppeteer), which Claude will then drive to perform the tasks described by the tester.

Claude has also come up with its latest update, 3.5, where the tool can perform actions similar to humans without any instructions. For instance, finding buttons, clicking them, and presenting the output in either browser logs or on the chat interface directly. However, this still has a long way to go and currently cannot be used in enterprise-level testing.

Creating Test Cases With LambdaTest Test Manager

Once the tests are generated, they need to be executed and, most importantly, managed regularly. In these situations, the team looks at the tools that provide services that are more than just prompt-based “input-output” features, and this is where LambdaTest AI-powered Test Manager comes into the picture.

LambdaTest provides a unified test manager that provides test case creation, management, triggering, and reporting all in one place. With LambdaTest Test Manager, you can create test cases manually or using AI.

For demonstration, let’s look at how to create test cases with AI:

Note: Ensure you have access to the Test Manager. If not, please contact sales.

1. From the top-right, click on the New Project button.



2. Enter your Project name, Description and Tag(s) in the respective fields.



3. Click on the Create button, and it takes you to the below screen.



4. Click on the project name that you just created, and the Test Manager will route you to the Test Cases dashboard.
5. Navigate to the prompt box and press the Tab key to generate test cases with AI. You can then press the Shift+Enter keys to generate multiple test cases. Once done, press the Enter key.

These test cases will be generated based on your project name.


You can then organize your test cases efficiently by creating folders and subfolders. Additionally, you can copy and move test cases, export test cases and do much more.

To get started, refer to this documentation on Introduction to Test Manager.

Note

Create and manage test cases with AI-powered Test Manager. Try LambdaTest Today!

Conclusion

Authoring tests in software testing is one of the most time-consuming jobs. The tester has to not only make sure the tests are maintainable and readable but also think about the coverage which sometimes can make things a bit complex. This challenge can be avoided by adopting AI in software testing to take care of the tasks that were performed manually.

It can be introduced at multiple levels, performing multiple types of jobs. Some might just be available to generate tests with AI, while some AI testing tools or test assistants like KaneAI can debug, fix errors, and generate test reports on their own.

Whatever method a tester opts for, AI is bound to get fabulous benefits and overcome the challenges of automation testing performed manually. It is a step ahead in getting an autonomous test infrastructure, something that we all aim for in the future.

Citations

Harish Rajora

I am a computer science engineer. I love to keep growing as the technological world grows. I feel there is no powerful tool than a computer to change the world in any way. Apart from my field of study, I like reading books a lot and write sometimes on https://www.themeaninglesslife.com .

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